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作 者:刘欣[1,2] 秦彦杰 冯晓淼[3] 朱苏加 LIU Xin;QIN Yanjie;FENG Xiaomiao;ZHU Sujia(Institute of Geographical Sciences,Hebei Academy of Sciences,Shijiazhuang 050011,China;Hebei Engineering Research Center for Geographic Information Application,Shijiazhuang 050011,China;Shijiazhuang College of Resources and Environmental Science,Shijiazhuang 050035,China)
机构地区:[1]河北省科学院地理科学研究所,石家庄050011 [2]河北省地理信息开发应用工程技术研究中心,石家庄050011 [3]石家庄学院资源与环境科学学院,石家庄050035
出 处:《科技导报》2020年第13期73-82,共10页Science & Technology Review
基 金:河北省软科学研究计划项目(194576121D);河北省社会科学发展研究课题(2019031203004,201803070602)。
摘 要:自然与人文多因素交织造成山区贫困差异显著,测定贫困-富裕度及驱动,可为山区脱贫致富提供决策支持。以县域为基本单元,从自然环境(A)、土地资源(B)、县域经济(C)、民众生活质量(D)和生计能力(E)5个维度选取33项指标建立指标体系,测度河北山区多维贫困-富裕度状况;引入贫困区位熵分析不同维度对贫困发生的影响;将二者进行空间耦合,找出贫困分布与主导维度的空间一致性与差异,并结合各维度主导因子探讨可持续生计策略。结果表明:研究区多维贫困发生率为89.52%,中度以上贫困发生率为62.50%,贫困程度深;空间分布上,中度和低度贫困连片多发,重度、富裕或相对富裕区分布分散;贫困驱动上,A和C维度主导的贫困发生率高于其他维度,重度贫困与A维度空间耦合度高,中度贫困与A、C维度空间一致。基于研究结果,提出生态搬迁、增加自然资源效益、土地和产业扶贫等差异化可持续生计策略。In mountainous areas, the regional difference of poverty is significant due to the interweaving of natural conditions and cultural factors. The determination of the poverty-affluence degree and the reasons can help to improve decision support for mountainous areas to get rid of poverty and become rich. This paper takes mountain counties in Hebei province as the basic unit. 33 indicators are selected from five dimensions. The natural environment(A), the land resources(B), the county economy(C), the people’s quality of life(D) and the livelihood ability(E) to construct a index system. And multidimensional povertyaffluence status is obtained in research area. The poverty location entropy is introduced to analyze the influence of each dimension on the occurrence of poverty. In order to discover the spatial consistency and differences between poverty-affluence distribution and dominant dimension, the two results are compared in space. And sustainable livelihood strategies are discussed with the dominant factors of each dimension. The results are as follows. the incidence of multidimensional poverty is 89.52% and above moderate poverty is 62.50%. The poverty level is deep in research area. In spatial distribution, moderate and low poverty degrees were frequent, while severe, rich or relatively rich areas are scattered. In poverty driver, the incidence of poverty dominated by A and C dimensions is higher than that of other dimensions. Severe poverty is highly coupled with A dimension,and moderate poverty is consistent with A and C dimensions. Basing on the results, the livelihoods strategies are put forward,such as the ecological relocation, an increase of the profit of the natural resources and getting rid of poverty through land and agricultural industry.
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